Sync 13 recordings from danielrosehill/Read-Aloud-Voice-Sentences

README.md

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+---
+license: cc-by-4.0
+language:
+- en
+task_categories:
+- automatic-speech-recognition
+pretty_name: Hard ASR Sentences
+tags:
+- speech
+- asr
+- fine-tuning
+- single-speaker
+- hard-asr
+- english
+size_categories:
+- n<1K
+configs:
+- config_name: default
+  data_files:
+  - split: train
+    path: data/train/**
+  - split: test
+    path: data/test/**
+---
+
+# Hard ASR Sentences
+
+English sentences speech recognition finds hard, read by one speaker: Harvard sentences (IEEE 1969, public domain), tongue twisters, homographs, garden-path sentences, rare words, dense numbers and units, unusual proper nouns. `prompt_kind` names the kind and `prompt_source` the origin of each sentence.
+
+**Website: [hebrish.app](https://hebrish.app)**: get the Hebrish keyboard for Android and the desktop apps, see the results, and find every model, dataset and demo in one place.
+
+**This is a subset of [`danielrosehill/Read-Aloud-Voice-Sentences`](https://huggingface.co/datasets/danielrosehill/Read-Aloud-Voice-Sentences)**, the full, undifferentiated
+dataset. It contains every phone recording there whose `categories` include `hard-asr` (the capture app's task of that name). Rows are copied
+unchanged, with the same ids, columns and train/test split, by `scripts/sync_subsets.py` in the
+project repository. Do not edit this dataset directly: fix the row in the main dataset and re-sync.
+The subset grows as new takes are published.
+
+**Speaker:** Daniel Rosehill, the dataset's author, who was born in Ireland and speaks English with an **Irish accent**, and who lives in Jerusalem. Every recording is his voice.
+
+All audio was recorded on a **OnePlus Nord 3 5G** phone using its **internal microphone**, with browser echo cancellation, noise suppression and auto gain turned off.
+
+## Layout
+
+```
+data/train/audio/<id>.wav    16 kHz mono 16-bit PCM
+data/train/metadata.jsonl
+data/test/...                held-out set, never trained on
+```
+
+The `test` split is **term-disjoint**: a held-out term never appears in `train`.
+`load_dataset("Hebrish/Hard-ASR-Sentences")` works directly.
+
+## Columns
+
+The columns are the same as in the main dataset: `text` (ground truth, punctuated and cased like
+Parakeet v2 output), `text_he` (the same transcript with its Hebrew terms in Hebrew script, for
+Hebrew-capable models), `categories`, `target_terms`, `prompt_source`, `prompt_origin` (manual / dataset / generated), `edited`, `duration_s`,
+`environment`, `conditions`, `device`, `speaker`, `speaker_gender`, `hebrew_pronunciation`, `variant_groups`, `variant_spelling` and `recorded_at`. The main dataset's card describes them.
+
+## Licence
+
+CC-BY-4.0, with sentence-text attribution per `prompt_source` as described in the
+[main dataset's licence section](https://huggingface.co/datasets/danielrosehill/Read-Aloud-Voice-Sentences#licence-and-attribution).

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